AI Engineer (Agentic AI)

ProwessIT Solutions LLC.; Shrewsbury (MA); Remote; USD 108,000 - 132,000; Full time

Job summary

ProwessIT Solutions LLC. is seeking an AI Engineer (Agentic AI) for a remote, long-term contract role in the United States.

You will design and build practical AI-driven solutions within a GCP environment, focusing on real-world use cases using LLMs, RAG architectures, and agentic workflows to enhance internal tools, automation, and data-driven applications.

Qualifications

• Hands-on AI/ML and LLM experience with OpenAI or Vertex AI.
• Experience with RAG techniques and agent-based workflows.
• Strong Google Cloud Platform experience (BigQuery, Dataflow, Vertex AI).

Responsibilities

• Design and build AI/LLM-based solutions, including RAG pipelines.
• Develop and prototype agentic AI workflows for automation and decisioning.
• Integrate LLM solutions with existing GCP data platforms (BigQuery, Dataflow).
• Work with structured and unstructured data to enable intelligent retrieval and insights.
• Create, test, and optimize prompt engineering strategies.
• Collaborate with backend and data engineering teams to embed AI capabilities into applications.

Skills

AI/ML

LLMs

RAG

Python

APIs

Google Cloud

LangChain

LlamaIndex

Tools

BigQuery

Dataflow

Vertex AI

LangChain

LlamaIndex

Job description

AI Engineer (Agentic AI)

Location: Remote in US

Duration: Long-term contract

Salary: $120,000/year

Description: We are looking for a hands‑on AI / LLM Engineer to help design and build practical AI-driven solutions within an existing GCP environment. This role will focus on developing real-world use cases using LLMs, RAG architectures, and agentic workflows to enhance internal tools, automation, and data-driven applications.

A strong candidate should be able to:

• Clearly explain an AI project they personally worked on.


• Explain the business problem/use case behind the project.


• Walk through their thought process from requirements through design and implementation.


• Explain why they selected specific technologies or architecture.


• Discuss their role and contributions without relying on generic or team-level answers.


• Think through a new use case logically and build a solution approach.


• Communicate confidently and naturally when challenged with follow-up questions.

Must Haves:

• Experience with AI/ML and LLMs (OpenAI, Vertex AI, or similar)


• Hands‑on experience with RAG (Retrieval‑Augmented Generation)


• Strong experience with Google Cloud Platform (BigQuery, Dataflow, Vertex AI preferred)


• Experience with AI orchestration tools (LangChain, LlamaIndex, or similar)


• Proficiency in Python (preferred) or backend development


• Experience with APIs and integrating AI into applications

Nice to Have:

• Experience building agent-based or multi-step AI workflows


• Familiarity with vector databases (Pinecone, Weaviate, Vertex AI Vector Search)


• Background in backend development (Java/Spring Boot)


• Experience working in data engineering environments

Key Responsibilities:

• Design and build AI/LLM-based solutions, including RAG pipelines


• Develop and prototype agentic AI workflows for automation and decisioning


• Integrate LLM solutions with existing GCP data platforms (BigQuery, Dataflow)


• Work with structured and unstructured data to enable intelligent retrieval and insights


• Create, test, and optimize prompt engineering strategies


• Collaborate with backend and data engineering teams to embed AI capabilities into applications

[phone]